Oct 13th, 2021
Are you just starting out with qualitative research? Or perhaps you have experience in other forms of qualitative research but want to learn a bit more about Thematic Analysis specifically? You’ve come to the right place. In this podcast we (three early career researchers) talk about our understanding and experiences of conducting Thematic Analysis (TA) with the help of NVivo Software. We delve under the umbrella term of TA to ask, what is TA? Why did it appeal to our different research projects? And, of course, no research project is complete without a few stumbling blocks along the way, so we talk about those as well.
To polish off and add a little extra shine to the podcast we include a short interview with Dr. Katherine Ashbullby, Lecturer in Psychology at the University of Exeter, who shares her knowledge and experience of TA with the benefit of her experience in the field.
NVivo QSR International (2021)
For more information about NVivo and a range of training resources visit the NVivo website:
Sandelowski M, Barroso J. (2003) Classifying the findings in qualitative studies. Qual Health Res. 13(7):905–923.
Braun V, Clarke, V (2019) Reflecting on reflexive thematic analysis, Qualitative Research in Sport, Exercise and Health, 11:4, 589-597, DOI 10.1080/2159676X.2019.1628806 [this paper was referred to as ‘the 2016 one’ by Emily in the podcast]
Braun V, Clarke V. (2021) Can I use TA? Should I use TA? Should I not use TA? Comparing reflexive thematic analysis and other pattern-based qualitative analytic
approaches. Couns Psychother Res.;21:37–47. https://doi.org/10.1002/capr.12360
Victoria Clarke has tweeted a useful twitter thread on the Big Q/small q qualitative distinction, which be accessed through the following link: https://twitter.com/drvicclarke/status/1444258228439764993?s=20
YouTube videos by Victoria Clarke on Thematic Analysis: https://www.youtube.com/channel/UCLBw6Qig8KBId9YuIMzAg7w
Kiger M.E., Varpio L. (2020) Thematic analysis of qualitative data: AMEE Guide No. 131, Medical Teacher, 42:8, 846-854, DOI: 10.1080/0142159X.2020.1755030
Contact and Feedback
This podcast is supported by the GW4 institutions – Bristol, Bath, Cardiff, and Exeter – as part of their NVivo Resource Development project, a pool of resources for researchers wishing to get started with NVivo software.
We hope that you enjoyed our podcast. We’d love to hear how you found it. Share your feedback with any of the GW4 doctoral college Twitter accounts:
@ExeterDoctoral @DoctoralBath @bristoldc
Thank you for listening!
A big thank you from us, Ailsa Naismith, Merve Mollaahmetoglu and Emily Taylor, for listening and we wish you all the best in your research endeavours.
00:00:09,210 --> 00:00:20,730
Hello and welcome to R, D and the In Betweens, a fortnightly podcast where we talk to guests about research, development and everything in between.
00:00:20,730 --> 00:00:31,380
This week is a special episode with three guest hosts, Ailsa Merve and Emily from the University of Bristol and Exeter.
00:00:31,380 --> 00:00:39,050
You're listening to a podcast on thematic analysis and how to tease meaning from qualitative data.
00:00:39,050 --> 00:00:41,960
If you're interested about thematic analysis,
00:00:41,960 --> 00:00:50,480
keep listening for some insights from three researchers from the University of Exeter and Bristol who have been through the process.
00:00:50,480 --> 00:00:58,160
We're also going to hear a little bit from an expert on thematic analysis who shares their key tips on the process.
00:00:58,160 --> 00:01:03,380
I'm Ailsa and I work at Earth Sciences at the University of Bristol.
00:01:03,380 --> 00:01:13,400
I'm here with Merve working in psychology and Emily, who works in the College of Medicine and Health, and both are at the University of Exeter.
00:01:13,400 --> 00:01:17,940
Hi there. Hi. Great.
00:01:17,940 --> 00:01:24,230
So lovely to chat today. And let's make some introductions.
00:01:24,230 --> 00:01:33,590
I myself am a volcanologist, and I started using thematic analysis to study how people remember past volcanic eruptions.
00:01:33,590 --> 00:01:41,930
How did both of you get into the topic from what backgrounds? Yes, my name is Merve and I'm in the psychology department.
00:01:41,930 --> 00:01:48,560
So I started using thematic analysis to understand experiences of people who were being ketamine for the treatment,
00:01:48,560 --> 00:01:52,790
who were being given ketamine for the treatment of alcohol use disorders.
00:01:52,790 --> 00:02:02,240
Yeah. How about you? I'm Emily and I use thematic analysis for my project looking at independent and older people.
00:02:02,240 --> 00:02:07,370
And this was a mixed method analysis. So I was using quantitative and qualitative data.
00:02:07,370 --> 00:02:13,860
So I found thematic analysis with some of its flexibility was really quite helpful for that.
00:02:13,860 --> 00:02:21,690
That's really interesting. It sounds like we're coming from very different backgrounds and using thematic analysis in different ways,
00:02:21,690 --> 00:02:35,220
but for those people who for those listeners who are not so familiar with thematic analysis, how would we define that message to them?
00:02:35,220 --> 00:02:36,480
That's a really good question.
00:02:36,480 --> 00:02:45,420
And I think one thing to understand is that thematic analysis is not a single method, but it's used as an umbrella term for a family of methods.
00:02:45,420 --> 00:02:52,980
And as Emily mentioned, it can be flexible in both theoretically, but also in the way that it can be used with inductive.
00:02:52,980 --> 00:02:59,400
So data driven and deductive, so theory driven approaches and approaches to coding.
00:02:59,400 --> 00:03:06,150
And it can also capture both semantics, explicit or latent implicit meanings and data.
00:03:06,150 --> 00:03:07,860
So what is actually thematic analysis?
00:03:07,860 --> 00:03:17,760
So it is a pattern based qualitative method and it's considered to belong to the phenomenological or experiential qualitative research tradition.
00:03:17,760 --> 00:03:25,410
So it tries to understand exploration of participants subjective experiences and making sense of their.
00:03:25,410 --> 00:03:34,410
I think the only thing I can think to add is some people would say it's sort of in the middle in terms of descriptive vs. interpretive.
00:03:34,410 --> 00:03:38,830
Some people would argue it can go any place on the scale depending on how you use it.
00:03:38,830 --> 00:03:44,730
But I think it can you sort of sit in the middle? Yeah, and I definitely agree with that.
00:03:44,730 --> 00:03:51,570
And I think that ties in with what Merve says about it could be an inductive or deductive
00:03:51,570 --> 00:03:59,160
approach that you kind of start with a you start with a theory of what you're expecting to see.
00:03:59,160 --> 00:04:03,990
And you might find that in your research you confirm that, or conversely,
00:04:03,990 --> 00:04:11,040
you might start with almost kind of no expectations of what you're going to find in your research.
00:04:11,040 --> 00:04:15,900
And then you build up your themes as you as you go along.
00:04:15,900 --> 00:04:23,340
And I think that that is one of the really good things about thematic analysis,
00:04:23,340 --> 00:04:32,100
the flexibility that you mention, Emily and Merve, you use this term of pattern based methods.
00:04:32,100 --> 00:04:39,710
I'm kind of interested in that. How could you elaborate on that pattern based, similar pattern based?
00:04:39,710 --> 00:04:45,150
I'm referring to qualitative analysis methods that focus on analysing patterns
00:04:45,150 --> 00:04:50,170
of meaning across data items or cases and a qualitative qualitative data set.
00:04:50,170 --> 00:04:54,510
So what I mean by data items are cases. I'm referring to participants.
00:04:54,510 --> 00:05:03,960
So call it a thematic analysis is one approach, one pattern based approach that others, such as qualitative content analysis,
00:05:03,960 --> 00:05:12,960
IPA, grounded theory, reflexive thematic analysis, the one I just mentioned, and also a pattern based discourse analysis.
00:05:12,960 --> 00:05:19,590
I guess pattern based methods are different than other qualitative methods that examine,
00:05:19,590 --> 00:05:25,110
for example, the more fine grained or interactional work of speech,
00:05:25,110 --> 00:05:33,390
such as conversation, analysis, or it's also different from methods that focus on biographies or stories such as narrative analysis.
00:05:33,390 --> 00:05:40,980
So that's how we can distinguish thematic analysis from other types of qualitative analysis approaches.
00:05:40,980 --> 00:05:46,080
Emily, did you have anything to add? No. Again, I think you've put it really well.
00:05:46,080 --> 00:05:58,320
I think one of the things about it being pattern based, so it also lends to it being a useful foundational tool for for other qualitative methods.
00:05:58,320 --> 00:06:08,280
So grounded theory and an IPA, I think both kind of expand on and of some of the concepts of thematic analysis,
00:06:08,280 --> 00:06:14,320
although thematic analysis is definitelu argued as a standalone method in itself.
00:06:14,320 --> 00:06:19,130
I just realised we haven't quite defined what it is, and for me, I initially forgot,
00:06:19,130 --> 00:06:24,850
well, not forgot, but it's quite a long road, so we should probably specify that.
00:06:24,850 --> 00:06:30,650
I think it's interpretative phenomenological analysis, just as a note to the listener.
00:06:30,650 --> 00:06:38,530
Yeah, good point. Very nicely pronounced. I'm always like shying away from saying it because it's such a long one.
00:06:38,530 --> 00:06:47,400
But yet when we say IPA, that's what we're referring to. Got you got you, not the IPA beer
00:06:47,400 --> 00:06:52,240
That would be a great type of uh. I'd be very interested. Yeah.
00:06:52,240 --> 00:06:58,150
Emily, I really liked what you picked up on in that thematic analysis can be kind of standalone,
00:06:58,150 --> 00:07:04,030
but it also is the foundation for a lot of different other types of analysis.
00:07:04,030 --> 00:07:10,990
I think that's really key and that for me in my research was something I instinctively felt.
00:07:10,990 --> 00:07:21,730
So I haven't done any other types of qualitative analysis than the analysis, but it kind of feels when you're doing it that it's so,
00:07:21,730 --> 00:07:27,970
so powerful and so flexible that you could really use it for and other other methods.
00:07:27,970 --> 00:07:35,500
And yeah, I wondered I mean, like I've said, I haven't done anything else apart from thematic analysis.
00:07:35,500 --> 00:07:47,350
But I wondered if you had both worked on some of these other methods that that you mentioned Merve and whether you wanted to kind of
00:07:47,350 --> 00:07:57,070
briefly elaborate on on how perhaps whether you liked them and whether thematic analysis itself really informed those other methods.
00:07:57,070 --> 00:08:06,820
So I will I am I have only really used thematic analysis, although I didn't really realise that it was counted as thematic analysis,
00:08:06,820 --> 00:08:10,570
because going back to the comment you made earlier is an umbrella term.
00:08:10,570 --> 00:08:18,340
So I actually use framework analysis, which if you go by and Clarke's definition,
00:08:18,340 --> 00:08:22,840
that would be counted as sort of a code book type of thematic analysis.
00:08:22,840 --> 00:08:30,280
And so that's just it's not as rigid as another form, which is coding reliability,
00:08:30,280 --> 00:08:40,660
which is very keen on having accurate codes that are repeatable and have different researchers.
00:08:40,660 --> 00:08:48,760
So that's kind of the key quality of coding reliability. And then you've got the bottom part version of reflexive analysis,
00:08:48,760 --> 00:08:56,830
which is much more recognising the generation and and sending of the researcher and the impact to the researcher on things.
00:08:56,830 --> 00:09:02,530
So a code book, which is where mine sits this framework is sort of in between those two,
00:09:02,530 --> 00:09:09,220
because it does have a framework which has some sort of deductive codes coming in to start with.
00:09:09,220 --> 00:09:16,040
And for me that was useful because that related to the mixed methods sort of side of my project that I,
00:09:16,040 --> 00:09:24,700
I did want to explore and sort of the more abstract and deeper kind of meanings within my studies.
00:09:24,700 --> 00:09:30,910
But I also needed to relate it to the quantitative work as well. So then use the deductive side for that.
00:09:30,910 --> 00:09:38,230
Mm hmm. That's so interesting, Emily. And I think that kind of brings us to a point that I wanted to mention about this,
00:09:38,230 --> 00:09:44,950
because we defined we said that thematic analysis is an umbrella term, but we haven't really quite defined what sits under that.
00:09:44,950 --> 00:09:51,280
And you refer to these sort of three main approaches within themantic analysis that Braun and Clark mentioned.
00:09:51,280 --> 00:09:53,860
So, you know, you said the coding reliability approaches,
00:09:53,860 --> 00:10:03,870
the reflexive approaches and the codebook approaches with that continuum from coding reliability to reflexive themantic analysis.
00:10:03,870 --> 00:10:08,080
And, yeah, I think that's an important distinction to make.
00:10:08,080 --> 00:10:13,930
And I think what I would add to that is that Braun and Clark refer to coding reliability.
00:10:13,930 --> 00:10:17,710
Thematic analysis is what's called a small q qualitative research.
00:10:17,710 --> 00:10:24,410
So when you use qualitative tools and techniques with a post positivist research values
00:10:24,410 --> 00:10:33,910
so sort of the research values that underpin quantitative research and emphasise sort of the objective and replicable knowledge as ideal,
00:10:33,910 --> 00:10:39,850
whereas the reflexive thematic analysis sits more within the big Q qualitative research
00:10:39,850 --> 00:10:45,640
which where qualitative research is not simply conceptualised as tools and techniques,
00:10:45,640 --> 00:10:49,350
what that means is qualitative, both in terms of techniques but also values.
00:10:49,350 --> 00:10:55,150
So I think that's a really interesting discussion. Yeah, that is an interesting discussion, rather.
00:10:55,150 --> 00:11:01,120
And I wanted to ask you a bit more about that, because I still find some of these terms a bit confusing.
00:11:01,120 --> 00:11:07,570
So you kind of said that the small q qualitative research is use qualitative tools,
00:11:07,570 --> 00:11:15,610
but you have values of, I'm guessing, understanding that there's maybe a objective truth out.
00:11:15,610 --> 00:11:16,750
There are things to learn,
00:11:16,750 --> 00:11:25,840
whereas the big Q qualitative would be both that you use the qualitative tools but also have a qualitative approach in that you say,
00:11:25,840 --> 00:11:30,910
well, the truth is subjective and this is my interpretation of what you said,
00:11:30,910 --> 00:11:36,350
but perhaps you can elaborate because it's always it's good to hear in your own words.
00:11:36,350 --> 00:11:42,220
I've just got a note here that the big Q is around encompassing the philosophy and procedure.
00:11:42,220 --> 00:11:51,460
And so sort of what you were saying. Yeah, I guess the point to make here is that there's the what is referred to as small q qualitative research,
00:11:51,460 --> 00:11:56,830
which uses maybe the quantitative research values within a qualitative method.
00:11:56,830 --> 00:12:04,870
And then there's the big Q qualitative research which where the methods and the values are aligned in qualitative research.
00:12:04,870 --> 00:12:08,320
Yeah, that's a really good way of putting it actually.
00:12:08,320 --> 00:12:15,670
And I guess you can see where you sit within this continuum of thematic analysis or qualitative research more generally,
00:12:15,670 --> 00:12:20,170
depending on what the needs of the research that you're conducting are.
00:12:20,170 --> 00:12:25,120
And I think the reference for that is from Sandelowski and Barroso in 2003,
00:12:25,120 --> 00:12:29,200
just from reading this morning that we might be able to put that in the notes.
00:12:29,200 --> 00:12:31,720
And you've also both mentioned Braun and Clarke.
00:12:31,720 --> 00:12:39,190
So I think this would be this is a really key article to it, kind of in reference for people to be able to look back on.
00:12:39,190 --> 00:12:45,910
It seems that I think all of us have found that a really useful resource from our very different backgrounds.
00:12:45,910 --> 00:12:51,820
I think one of the really interesting things about Braun and Clark is that they do they have the original paper in 2006,
00:12:51,820 --> 00:12:56,610
but they have done lots of papers since and encourage you to read those papers because they.
00:12:56,610 --> 00:13:05,790
You reflect on what how they've learnt to learn from teaching about as well, and I think that makes and is really helpful,
00:13:05,790 --> 00:13:15,420
but also quite informative for a new researcher to realise actually there was all this reflection and all of this has gone before.
00:13:15,420 --> 00:13:22,710
Yeah, definitely, if you're just starting with qualitative research, don't just go and read their paper from 2006, that was 15 years ago.
00:13:22,710 --> 00:13:28,650
And there they have so many more papers come out since then that are really informative.
00:13:28,650 --> 00:13:33,210
So I think that's one of the most referenced papers in the whole world.
00:13:33,210 --> 00:13:35,580
I'm not entirely sure it's about hundred thousand times.
00:13:35,580 --> 00:13:43,540
But, you know, I think they also emphasise that things have moved on from the their understanding at that time.
00:13:43,540 --> 00:13:51,470
So I would definitely recommend reading some of their most recent papers, which we can link in the show notes as well.
00:13:51,470 --> 00:13:57,710
This is a mad numbers of references. Yeah, it's crazy, but it's also, I think,
00:13:57,710 --> 00:14:07,220
confidence building that these people who have written such a seminal resource have also shown that in their subsequent papers,
00:14:07,220 --> 00:14:09,260
they've been pretty reflexive.
00:14:09,260 --> 00:14:21,890
The because this is kind of a theme or a common feature of thematic analysis itself that's kind of going over and and refining looking back on.
00:14:21,890 --> 00:14:29,070
So to have some of the most prominent practitioners of it do it in their own work and in their own understanding,
00:14:29,070 --> 00:14:37,910
that's pretty, pretty great, I think.
00:14:37,910 --> 00:14:48,770
I just want to say one other aspect perhaps that we haven't discussed in terms of thematic analysis is, is the issue of method versus methodology.
00:14:48,770 --> 00:14:55,700
And I think before I started doing qualitative research, before I started being involved with qualitative research,
00:14:55,700 --> 00:14:59,210
I kind of assumed method and methodology were the same thing.
00:14:59,210 --> 00:15:07,110
So I kind of used interchangeably. But they actually refer to different things and I think it would be really useful for people to know.
00:15:07,110 --> 00:15:15,690
And so the way methodology is defined is that methodology refers to theoretically informed frameworks for research.
00:15:15,690 --> 00:15:21,470
So this include things like IPA discourse, analysis, and on the other hand,
00:15:21,470 --> 00:15:29,000
method refers to technically it's sort of not technically, theoretically independent tools and techniques such as thematic analysis.
00:15:29,000 --> 00:15:38,630
So, you know, from the examples that we've given earlier about pattern based methods from pattern based methods and methodologies,
00:15:38,630 --> 00:15:45,140
thematic analysis and qualitative content analysis are are considered pattern based methods.
00:15:45,140 --> 00:15:54,020
So these offer people, researchers, tools and techniques that are either a theoretical or theoretically flexible in the case of thematic analysis,
00:15:54,020 --> 00:16:01,610
for example, and things like IPA, grounded theory, discourse, analysis, these are considered methodology.
00:16:01,610 --> 00:16:09,230
So these have theoretically informed framework's research. That's an important distinction to clarify for people.
00:16:09,230 --> 00:16:18,590
Yeah, Merve I think you nailed it. I mean, I, I still struggle with method versus methodology, but I think that's that's quite clear.
00:16:18,590 --> 00:16:22,630
And for me, it's kind of useful, you know, like what's in an ology
00:16:22,630 --> 00:16:34,700
Like, what's the difference that I think I think I mean, one one one thing that's just occurred to me as as you describe that Merve is that,
00:16:34,700 --> 00:16:40,010
you know, the set method, as I understand it, is theory.
00:16:40,010 --> 00:16:45,510
So you said it's the theoretically independent. So I could approach that with different research philosophies.
00:16:45,510 --> 00:16:53,240
Yes. And the methodology is is informed by a particular research philosophy.
00:16:53,240 --> 00:17:00,290
I think in a way like what Emily said was really helpful in understanding that themantic analysis is theoretically flexible because, you know,
00:17:00,290 --> 00:17:06,290
she said how she adapted it to suit the needs of her research project in the
00:17:06,290 --> 00:17:11,330
sense that she still needed things to be reliable and replicable in a sense.
00:17:11,330 --> 00:17:18,740
So she didn't use perhaps the reflexive thematic analysis, which doesn't necessarily concern itself with reliability.
00:17:18,740 --> 00:17:26,750
And it understands that themes are quite subjective. So it doesn't try to reduce that research researcher bias.
00:17:26,750 --> 00:17:33,360
So, you know, she's adopted the thematic analysis to her research values and philosophy.
00:17:33,360 --> 00:17:35,430
00:17:35,430 --> 00:17:45,270
Yeah, yeah, I really I keep coming back to that that that thing you said the start, I believe, how you liked the flexibility of thematic analysis.
00:17:45,270 --> 00:17:52,030
And I also in my research, that was a really big pool for me because I had this this.
00:17:52,030 --> 00:17:56,580
Yeah, I just I just wanted to have a powerful tool that could do what I wanted it to do.
00:17:56,580 --> 00:18:08,760
So, yeah. And I wanted to ask if there were other other appeals of thematic analysis that really led you to choose it to to analyse your research.
00:18:08,760 --> 00:18:16,830
That's a good question, I think. It sort of led me on to think of something else, which may not be quite answering the question,
00:18:16,830 --> 00:18:25,770
but I think it's sort of relevant and I don't want to ask again, I think it's a 2016 paper.
00:18:25,770 --> 00:18:32,970
They talk about and using it as a tool to be used flexibly, but also with knowingness.
00:18:32,970 --> 00:18:38,190
So and thinking about although it can be flexible with the very thinking about
00:18:38,190 --> 00:18:42,750
what I still think about what's underpinning it and how you're using that.
00:18:42,750 --> 00:18:46,650
And for me, this it just worked.
00:18:46,650 --> 00:18:52,470
And I think the conversation it was having going on in my research is looking
00:18:52,470 --> 00:18:58,440
at the quantitative and qualitative and how they speak to each other or not,
00:18:58,440 --> 00:19:05,610
and the fact that I could use a guess sort of deductive and inductive within that analysis.
00:19:05,610 --> 00:19:09,150
And also the fact is looking at patterns so I can only see other patterns
00:19:09,150 --> 00:19:16,440
between the two types of data and what a contrast and just works well for me,
00:19:16,440 --> 00:19:25,200
I think. Mm hmm. I think what I wanted to also say is something that Emily said is that it can do both.
00:19:25,200 --> 00:19:33,930
It sort of sits between descriptive and analytical approaches. And again, that fits within more descriptive, more themantic approach,
00:19:33,930 --> 00:19:44,010
a systematic analysis versus more light and versus approaches that try to on the cover more detail and implicit meanings.
00:19:44,010 --> 00:19:49,410
So I think that's some other benefit of thematic analysis that you can sort of do both of those things with it.
00:19:49,410 --> 00:19:51,430
Yeah, yeah, I like that.
00:19:51,430 --> 00:19:59,790
So I imagine that if you're under covering a theme, a theme could be something that someone's kind of one of your, let's say, an interview.
00:19:59,790 --> 00:20:06,660
He says something that you say, well, this can't this text can be taken as read a descriptive theme or it's kind of
00:20:06,660 --> 00:20:11,850
the meaning behind the words is the kind of latent thing that you pick up.
00:20:11,850 --> 00:20:12,900
00:20:12,900 --> 00:20:21,510
Emily, from your your what you described, it sounds like you like the flexibility, but there was also some kind of structure underpinning it.
00:20:21,510 --> 00:20:25,710
So you didn't kind of just jump in and say, oh, I'm going to do whatever,
00:20:25,710 --> 00:20:31,350
but that you use thematci analysis to kind of marry that quantitative and qualitative analysis.
00:20:31,350 --> 00:20:46,860
And I really like that. I think that's. Yeah, a really, really positive thing of thematic analysis.
00:20:46,860 --> 00:20:56,440
So one thing I was going to go on to after that was that I think that we all use the software NVivo, for for thematic analysis.
00:20:56,440 --> 00:21:07,530
And I wondered if you felt that it was easy to kind of marry the analysis of the different qualitative and quantitative data in NVivo
00:21:07,530 --> 00:21:14,980
And that's also a good question. It certainly works well, I think can be very for me, it works how I think.
00:21:14,980 --> 00:21:23,640
So if I had a word my interview transcripts in paper form, I would probably be highlighting and then putting little notes in the margin.
00:21:23,640 --> 00:21:29,040
And actually, NVivo allows me to do that because I can highlight it and then make annotations.
00:21:29,040 --> 00:21:33,540
Or if I'm actually thinking about organising it, I can highlight to encode it.
00:21:33,540 --> 00:21:39,130
And that works. I believe it's a quantitative code or a qualitative code.
00:21:39,130 --> 00:21:46,020
Yeah. So it just works for me. And the benefit of and we believe we're doing that on paper is that I can then
00:21:46,020 --> 00:21:50,340
take those bits that I've coded and move them around and look at them together.
00:21:50,340 --> 00:21:59,010
Hmm. I mean, it's a great tool, isn't it, because, you know, before computers and NVivo, I imagine people had to do this by hand.
00:21:59,010 --> 00:22:09,270
And I think they would print out the interviews and they would highlight cut and paste, move around, you know, the whole floor being covered by paper.
00:22:09,270 --> 00:22:14,460
And, you know, I guess in a way you might become more involved with your data,
00:22:14,460 --> 00:22:20,640
but it also is very difficult to manage and share with other people and also very prone to getting lost.
00:22:20,640 --> 00:22:24,540
So and we were kind of does all of that in a computer system.
00:22:24,540 --> 00:22:31,710
And I think it's really helpful in terms of collaborating with people, because we know that, you know, in most qualitative research,
00:22:31,710 --> 00:22:36,780
interviews are coded by more than one people one person, one researcher,
00:22:36,780 --> 00:22:42,870
or even if it is just coded by you, you still probably want to share it with other people.
00:22:42,870 --> 00:22:46,410
So it's a great tool for facilitating facilitating that.
00:22:46,410 --> 00:22:49,500
Yeah. So there's a lot of tools around how to work with other people.
00:22:49,500 --> 00:22:57,970
And this is one of the tools that we've created for the for the enviable resources as part of the GW4 network.
00:22:57,970 --> 00:23:00,300
So if you are in one of those institutions,
00:23:00,300 --> 00:23:07,170
you will be able to access access some information about how to facilitate collaboration on NVivo as well, which we will link to at the end.
00:23:07,170 --> 00:23:08,190
Yeah, I love that.
00:23:08,190 --> 00:23:17,830
My personal experience I remember the first my very first getting into thematic analysis and having only three interviews to analyse,
00:23:17,830 --> 00:23:25,020
but the transcripts werfe each like 20 pages long. And before I got to use NVivo, I was just like, you know, writing down texts and stuff.
00:23:25,020 --> 00:23:32,190
And I had I think I had interesting themes, but it was like impossible to organise that or to get a sense of,
00:23:32,190 --> 00:23:40,290
you know, what was significant or what was just, you know, a kind of small idea, what could be descriptive.
00:23:40,290 --> 00:23:41,930
And I think in particular,
00:23:41,930 --> 00:23:52,530
the kind of latent themes for me were much harder to to to tease out and to understand when I just had big stacks of paper coming.
00:23:52,530 --> 00:24:06,090
And for me, uploading these transcripts into and being able to organise themes through notes and kind of linked them was like really a game changer.
00:24:06,090 --> 00:24:12,900
Yeah. Was it the same for you? Every. Yeah, yeah, there's a couple of things you said that it made me think I mean,
00:24:12,900 --> 00:24:16,510
I find it really helpful that you can sort of have everything in one place.
00:24:16,510 --> 00:24:25,710
You can have you can use memos to be to maybe reflexive memos or so you can have a project log, as almost, maybe your diary.
00:24:25,710 --> 00:24:27,630
And because I don't know if you're anything like me,
00:24:27,630 --> 00:24:34,440
but we have bits of paper everywhere that have little notes that you can have it all on and NVivo, which is quite handy.
00:24:34,440 --> 00:24:44,310
And also, um, I'm a very visual thinker. So some of the visualisation tools, that computer has had been really helpful, I think.
00:24:44,310 --> 00:24:46,560
Mm hmm. Yeah, I was just about to mention that.
00:24:46,560 --> 00:24:52,530
And I think another really cool tool is if you're using thematic analysis with a more quantitative approach,
00:24:52,530 --> 00:24:56,670
let's say you can run coding comparison a query.
00:24:56,670 --> 00:25:04,800
So if you have multiple people coding on the same project, you can automatically compare how much do they agree in terms of their coding?
00:25:04,800 --> 00:25:08,850
And you can highlight differences and you can highlight areas where they disagree.
00:25:08,850 --> 00:25:15,060
But it can be really useful tool to enable comparisons of integrated reliability and things like that.
00:25:15,060 --> 00:25:22,710
That's really useful to know because I have only ever coded as a I've only ever
00:25:22,710 --> 00:25:29,940
coded so low that going forward it could be a really useful thing to be able to,
00:25:29,940 --> 00:25:38,880
again, kind of reflect on whether these systems are robust, if other researchers involved are kind of seeing those who are picking them out.
00:25:38,880 --> 00:25:44,490
And if not, then there's an interesting dialogue to be had there with other researchers.
00:25:44,490 --> 00:25:48,600
And yeah, but I have I have also used the visualisation tools.
00:25:48,600 --> 00:26:00,020
I don't know if both of you use, but I'm a particular fan of the word clouds.
00:26:00,020 --> 00:26:06,470
I mean, talking about, you know, we've talked a lot about all the benefits of thematic analysis,
00:26:06,470 --> 00:26:15,140
and I think listeners will be able to tell that we're all fans. But I know that with everything there comes some challenges.
00:26:15,140 --> 00:26:26,330
And for instance, I found initially that it was quite difficult to know how much significance to ascribe to a theme that was emerging in my data.
00:26:26,330 --> 00:26:34,400
And I wanted to ask you both, you know, any particular challenges that you've come across while doing thematic analysis?
00:26:34,400 --> 00:26:43,340
Yeah, I think that's a good point about describing how much weight to ascribe to the different bits of coding,
00:26:43,340 --> 00:26:48,620
and especially where we've talked about coming from Quantitative maybe a more quantitative background where
00:26:48,620 --> 00:26:54,200
you may be looking at Frequency's and things like that and actually realising that in thematic analysis,
00:26:54,200 --> 00:27:01,490
actually some of the very important and possibly the richest themes can be ones that don't appear all that often.
00:27:01,490 --> 00:27:03,860
But they they're really potent when they do.
00:27:03,860 --> 00:27:11,540
And they might also encourage you to explore a bit more into the other of the transcripts as well to see whether it does actually come up.
00:27:11,540 --> 00:27:16,760
It might just have been a bit more subtle than some of the others. That's really interesting.
00:27:16,760 --> 00:27:27,050
I guess for me, one of the challenges was getting my head around sort of this distinction between what's referred to as themes and domain summaries,
00:27:27,050 --> 00:27:34,640
especially within reflexive thematic analysis. So now now I do understand what domain summaries are.
00:27:34,640 --> 00:27:41,840
So domain summaries are basically a summary of what's been said, everything that's been said about a particular topic.
00:27:41,840 --> 00:27:46,670
So, for example, if I asked the participants a question, I might have asked something like,
00:27:46,670 --> 00:27:50,660
what are some of the negative experiences you've had with this treatment?
00:27:50,660 --> 00:27:55,280
And if I just summarise everything that said, that would be a domain summary,
00:27:55,280 --> 00:28:00,080
but it doesn't actually uncover the latents meanings behind what they've said.
00:28:00,080 --> 00:28:05,360
So the themes now I understand within reflect systematic analysis.
00:28:05,360 --> 00:28:14,780
The themes are sort of uniting the more implicit and or latent meanings behind what people have said, not just summarising what everyone has said.
00:28:14,780 --> 00:28:20,810
So, for example, a list of people have reported these as negative effects of the treatment sort of thing.
00:28:20,810 --> 00:28:31,460
So initially that was quite a challenge for me. But again, there are some useful resources around this as well, which we can link to.
00:28:31,460 --> 00:28:34,640
We're going to have so many links in the show. Great.
00:28:34,640 --> 00:28:49,190
Yeah, I think one other challenge I had starting off with is that I had some research questions that I think were led by my my certain approach,
00:28:49,190 --> 00:29:00,860
feeling that I feeling that I when I was coding my data, I wasn't actually getting answers that matched particularly well to the questions.
00:29:00,860 --> 00:29:06,380
And so initially that that felt quite worrisome.
00:29:06,380 --> 00:29:16,580
And then I think that what was helpful was understanding that the the themes that were emerging could then inform the questions.
00:29:16,580 --> 00:29:23,410
And in my case, I was able to do more interviews to then kind of revise the question.
00:29:23,410 --> 00:29:26,180
So, again, it was that thing that, you know,
00:29:26,180 --> 00:29:34,850
just because the things didn't necessarily answer exactly the questions that I had posed, that didn't mean that they're wrong.
00:29:34,850 --> 00:29:40,850
It was a case of of kind of recasting things, you know, re re.
00:29:40,850 --> 00:29:46,460
Yeah, recreating things and reflecting to understand that things could change.
00:29:46,460 --> 00:29:54,170
So I'd say moving from a kind of fixed mindset of, you know, the my hypothesis is wrong,
00:29:54,170 --> 00:29:58,970
which as a as a natural scientist, that is kind of that is the approach that we take.
00:29:58,970 --> 00:30:04,010
And it's like a very ingrained thing that we don't really reflect on research philosophy at
00:30:04,010 --> 00:30:10,190
all to meeting something that was like a lot more reflective and a lot more understanding
00:30:10,190 --> 00:30:20,030
of the subjectivity of meaning and of experience that I think is really key to thematic
00:30:20,030 --> 00:30:27,260
analysis and for me and maybe for you guys too really attractive to this kind of research.
00:30:27,260 --> 00:30:34,400
And I think in a way, what you're saying is that your research questions were informed by your data as well,
00:30:34,400 --> 00:30:38,570
rather than the other way around, which usually is the case with quantitative research.
00:30:38,570 --> 00:30:44,360
You have a theory which informs the research questions and then you get the data to support or not supported,
00:30:44,360 --> 00:30:50,490
whereas here you got some data and that led you to revise your research questions.
00:30:50,490 --> 00:31:01,200
Yes, exactly. Nail on the head. And that is a really exciting for me everything exciting new ways to do research.
00:31:01,200 --> 00:31:09,020
Yeah. I think one one interesting thing about qualitative research generally is that it can generate a lot of hypotheses.
00:31:09,020 --> 00:31:17,240
Right. So I think that's one of the things that I've enjoyed so much about being involved in qualitative research is that you get such a deep insight
00:31:17,240 --> 00:31:26,450
into a topic and it can sort of generate more questions for research that either you answer with qualitative or with quantitative research.
00:31:26,450 --> 00:31:36,170
Yeah, I think, you know, so your example was sort of just thinking about deductive and inductive that the deductive is it can be very useful
00:31:36,170 --> 00:31:42,080
sometimes to kind of if you really need to pinpoint a particular aspect and you've got that in your question.
00:31:42,080 --> 00:31:50,090
But actually the inductive has that place to explore a bit further and may deviate from actually what that initial question was.
00:31:50,090 --> 00:31:52,580
But as you say, it's just that much more informative.
00:31:52,580 --> 00:32:01,610
And it's one of the I think one of the as it if it was one of the joys of qualitative research and how it can be really informative.
00:32:01,610 --> 00:32:06,560
You're so right. And it's it's cool to think of OK to think of it as an ongoing process.
00:32:06,560 --> 00:32:17,180
I think that that it's not kind of done and dusted it can kind of continually we can continually learn more and ascribe more meaning.
00:32:17,180 --> 00:32:23,570
Absolutely. I think there's several cases where it's been, you know, actually, although there might be steps,
00:32:23,570 --> 00:32:33,020
I think one of the papers we're looking at gets six steps to to or I think it's the reflectivity.
00:32:33,020 --> 00:32:38,660
But actually, although it might be presented as six steps, though, things are very much you kind of go cyclical,
00:32:38,660 --> 00:32:47,750
you might get to step two and then have to go back to that one and you might just kind of keep reinforcing or learning more so it develops as you go,
00:32:47,750 --> 00:32:55,130
which I think is very important as well. And that is part of the adding depth and richness to to your data as well.
00:32:55,130 --> 00:33:01,670
Definitely, yeah. I think before we wrap up, I just wanted to add something that might be reassuring to people.
00:33:01,670 --> 00:33:09,380
You know, if you're sort of thinking, is thematic analysis the right choice for me or, you know, how do I choose a type of analysis?
00:33:09,380 --> 00:33:14,090
I think what I found really interesting reading in one of Braun and Clark's paper,
00:33:14,090 --> 00:33:17,730
they're basically that they have a wealth of knowledge in this area.
00:33:17,730 --> 00:33:24,740
So we refer to them a lot. But I think they say that considering and choosing an analytical approach is sort of more like
00:33:24,740 --> 00:33:29,810
deciding between which type of fruit you will choose to eat rather than deciding whether
00:33:29,810 --> 00:33:32,220
to have fruit a slice of cake or a burger.
00:33:32,220 --> 00:33:41,330
So they kind of emphasise that a lot of different pattern based methods for examples, for example, can have very similar outputs.
00:33:41,330 --> 00:33:47,690
So it is an important decision, but it's not choosing between an apple and a burger,
00:33:47,690 --> 00:33:53,940
but it's more choosing between the types of fruits, which I find quite a reassuring analogy.
00:33:53,940 --> 00:33:58,460
Yeah, I like that one. Yeah, great. For someone is indecisive as me.
00:33:58,460 --> 00:34:01,700
That's very helpful. Yeah. And I guess yeah.
00:34:01,700 --> 00:34:08,840
There's a lot of resources around how to choose between different types of different types of pattern based methodology,
00:34:08,840 --> 00:34:12,010
methods or methodologies, and there are similarities and differences.
00:34:12,010 --> 00:34:21,560
So I think one of their papers was comparing thematic analysis to different types of other types of pattern based methods or methodology,
00:34:21,560 --> 00:34:26,800
which can be quite useful for some people to read. So we will link that as well.
00:34:26,800 --> 00:34:36,640
Definitely, we'll we'll put that in the show notes, and so I think we'll wrap up there because it's been a really lovely and informative
00:34:36,640 --> 00:34:42,460
discussion and we've talked around various aspects of thematic analysis,
00:34:42,460 --> 00:34:48,820
how we first came to you to join it or how we first came to use it in our research and the the
00:34:48,820 --> 00:34:55,600
benefits and some of its challenges and also some of the definitions of thematic analysis.
00:34:55,600 --> 00:35:02,860
And for me, it's been a real pleasure to to host this and to share with you guys a really great discussion.
00:35:02,860 --> 00:35:09,960
So I'd like to thank both of you. Oh, thank you. Yeah, it's been really interesting talking to you both about this.
00:35:09,960 --> 00:35:13,430
I really enjoyed it. Thank you. Oh, it's lovely.
00:35:13,430 --> 00:35:20,420
And, yeah, we've we've learnt a huge well, I personally learnt a huge amount and hope the listeners have to.
00:35:20,420 --> 00:35:25,940
But as we've said at various points through the podcast we have,
00:35:25,940 --> 00:35:32,810
we will include a link in links in the show, notes to all of the resources that we've mentioned.
00:35:32,810 --> 00:35:44,680
So, again, a huge thanks to Merve and Emily for our conversation.
00:35:44,680 --> 00:35:50,980
I have Dr. Kat Ashbullby with me right now. She's a lecturer in psychology at the University of Exeter.
00:35:50,980 --> 00:35:55,990
Kat, would you like to tell us a little bit about yourself? Hi, thank you so much for having me.
00:35:55,990 --> 00:36:02,770
So, yeah, so I'm a lecturer in psychology at the university and I did all my training at Exeter as well.
00:36:02,770 --> 00:36:05,830
And I'm really interested in qualitative methods.
00:36:05,830 --> 00:36:13,180
A lot of my research has involved qualitative work and my background is in something called economic psychology,
00:36:13,180 --> 00:36:17,830
which is how people make decisions about everyday financial life.
00:36:17,830 --> 00:36:22,150
So things like spending behaviour, saving behaviour, money and relationships.
00:36:22,150 --> 00:36:29,530
And then after my PhD, I worked in outside academia in a charity as well, doing research about health and wellbeing at work.
00:36:29,530 --> 00:36:34,360
So I've had an opportunity to work in different areas using qualitative research.
00:36:34,360 --> 00:36:39,520
Yeah, great. And the way we know each other is obviously you've been really helpful in our qualitative
00:36:39,520 --> 00:36:47,140
project and you have a lot more expertise in this topic than I do or any of us do.
00:36:47,140 --> 00:36:56,170
And so we have this we're having this podcast to give a bit of our resource to postgraduate researchers who want to get into qualitative research,
00:36:56,170 --> 00:37:02,680
specifically thematic analysis. And so we have had some definitions of thematic analysis.
00:37:02,680 --> 00:37:06,280
But I wonder if you could give us like a brief definition in your own words?
00:37:06,280 --> 00:37:16,450
Yeah, of course. A thematic analysis is perhaps best understood as like an umbrella term for different approaches to making sense of qualitative data.
00:37:16,450 --> 00:37:22,900
So there's some really nice resources that you can find online, actually, through Victoria Clarke, like on YouTube, for example,
00:37:22,900 --> 00:37:29,350
where she talks about the different types of thematic analysis that might be helpful for some of your sort of listeners to go to.
00:37:29,350 --> 00:37:37,330
But really, it's just the idea that you're making sense of qualitative data through identifying themes is the very sort of base level.
00:37:37,330 --> 00:37:40,600
But then when you go into it, that's kind of different ways of doing that,
00:37:40,600 --> 00:37:45,280
whether you're doing it in terms of like what you might have heard of a code book,
00:37:45,280 --> 00:37:49,180
thematic analysis, where you've got kind of the more a description already,
00:37:49,180 --> 00:37:57,160
even before you've looked at your data of what you might want to find or like what is this more reflexive organic approach where
00:37:57,160 --> 00:38:03,880
you're much more open to the data when you're going through is on a line by line basis looking at what the people are saying.
00:38:03,880 --> 00:38:09,160
So you've got no idea before you start what your what your findings will be.
00:38:09,160 --> 00:38:14,770
And that's quite different to the kind of code book approach where you might already have an idea of what your themes would look like.
00:38:14,770 --> 00:38:20,290
So there are these kind of differences within it. But yes, it's all about making sense of qualitative data.
00:38:20,290 --> 00:38:29,440
So whether that be from interviews or focus groups or an online source, yeah, that's reassuring that it matches up with what we discussed.
00:38:29,440 --> 00:38:36,610
Yeah, that's great. Thank you. And I guess our perspective in this podcast has been from three researchers have mainly trained in
00:38:36,610 --> 00:38:43,240
quantitative research methods and coming into qualitative research methods later on in our research journeys.
00:38:43,240 --> 00:38:45,370
So I wondered, in your experience,
00:38:45,370 --> 00:38:52,370
what are some of the common mistakes people might make when they're using thematic analysis, for example, in our position?
00:38:52,370 --> 00:38:56,950
Yeah. So I guess like from a positive starting point that is accessible,
00:38:56,950 --> 00:39:01,840
the masterclasses people from different backgrounds, I suppose there are like common, I guess,
00:39:01,840 --> 00:39:06,280
mistakes people make in the it's getting used to like working in a completely different way,
00:39:06,280 --> 00:39:08,980
isn't it, with the different kinds of language of research.
00:39:08,980 --> 00:39:16,870
So you're moving away from talking about kind of variables and control to talking about people's lived experiences.
00:39:16,870 --> 00:39:21,160
So I guess that's something that just people not aren't necessarily always used to, you know,
00:39:21,160 --> 00:39:29,260
moving away from the research tradition that they've been in to kind of open their eyes to a new way of doing research in terms of make mistakes.
00:39:29,260 --> 00:39:33,940
I guess maybe, you know, like we've just talked about, that definition of thematic analysis,
00:39:33,940 --> 00:39:38,290
I guess sometimes is some lack of understanding that it can actually be this umbrella term,
00:39:38,290 --> 00:39:42,340
that there are quite different things that you can do as kind of one thing.
00:39:42,340 --> 00:39:47,530
So I guess familiarise yourself with the different approaches to try and doing a bit more reading around.
00:39:47,530 --> 00:39:55,420
It's really helpful, I guess, as well. Also, sometimes people maybe underestimate the amount of work involved.
00:39:55,420 --> 00:40:00,730
So and I guess you know yourself from having done it, some people think it's just quite, very quick that you just,
00:40:00,730 --> 00:40:05,950
you know, suddenly have these themes, whereas in reality, it's actually quite a lot of work, isn't it?
00:40:05,950 --> 00:40:11,230
First we'll get the transcription and then code the data and then this kind of intrusive nature that
00:40:11,230 --> 00:40:16,210
you're going back between the data and your codes and developing it and the work that goes into that.
00:40:16,210 --> 00:40:25,390
People might underestimate Definitely And I think especially with the reflexive analysis, there's a lot of interpretative work that's involved.
00:40:25,390 --> 00:40:29,470
And yeah, and perhaps I might have made the same mistake in that thinking.
00:40:29,470 --> 00:40:33,640
It was a lot more descriptive than. Yeah, it really is.
00:40:33,640 --> 00:40:37,780
Yeah, yeah. Yeah. So definitely. So I guess that's another one isn't it, that that kind of take.
00:40:37,780 --> 00:40:42,680
So people get to the stage where they kind of got this descriptive sort of piece about their.
00:40:42,680 --> 00:40:47,380
That it's taking at the next level of them, putting those things together to say, first of all, my key findings,
00:40:47,380 --> 00:40:55,220
what does this mean in relation to my research question and Braun and Braun and Clark talk about the like, storybook theme.
00:40:55,220 --> 00:41:00,700
So that idea that you're really telling a story with your research first is kind of the bucket themes,
00:41:00,700 --> 00:41:04,270
which is more like just shoving everything in there that, you know.
00:41:04,270 --> 00:41:11,470
So it's kind of a storybook thing where you're trying to say, you know, what's really going on here with my with my findings.
00:41:11,470 --> 00:41:16,390
That's really interesting. It reminds me of something that we discussed when we were doing the qualitative
00:41:16,390 --> 00:41:21,490
analysis together about the difference between the domain summaries and the themes
00:41:21,490 --> 00:41:27,220
And I did mention this as one of the difficulties that I initially found with thematic in the podcast.
00:41:27,220 --> 00:41:33,370
But I wondered maybe if you can sort of give a more elaborate description of what that means.
00:41:33,370 --> 00:41:37,080
Yeah, I can try. Now, you did a really good job, though, with your paper, didn't you?
00:41:37,080 --> 00:41:45,520
And so I think it was more like, you know, say with the Ketamine paper, you had, like, for example, all the different things that people experienced.
00:41:45,520 --> 00:41:51,670
And and that's kind of if you're just writing that all down, that's kind of like what some people call like a domain summary.
00:41:51,670 --> 00:41:53,830
It's like all different things that happened.
00:41:53,830 --> 00:42:00,040
But then taking that next level was then looking at, OK, so maybe these were really contradictory things.
00:42:00,040 --> 00:42:05,380
These are about transformation. So it's like then those labels of like contradiction or transformation,
00:42:05,380 --> 00:42:09,300
which then become your themes in themselves rather than the list of experiences.
00:42:09,300 --> 00:42:12,550
It's like taking in the next level. That makes sense. Yeah, yeah.
00:42:12,550 --> 00:42:16,360
That's a really good description. And so what would you advise?
00:42:16,360 --> 00:42:23,560
I think you sort of answered this, but what would you advise quantitatively, researchers who are new to qualitative methods or thematic analysis?
00:42:23,560 --> 00:42:29,680
Yeah, what I think doing some like, you know, more study or more reading, like I said, there's some really good online resources.
00:42:29,680 --> 00:42:38,090
So Victoria Clarke has been really influential in, like, kind of defining and delineating what thematic analysis is.
00:42:38,090 --> 00:42:41,140
And she's got some really nice YouTube videos that are quite straightforward
00:42:41,140 --> 00:42:45,020
just to watch to introduce you to some of these things about thematic analysis.
00:42:45,020 --> 00:42:48,670
And there's also a lot of like papers around that as well that they've done recently,
00:42:48,670 --> 00:42:53,090
just talking about different stages of their analysis, I guess, as well.
00:42:53,090 --> 00:42:57,700
It's just about being open to a new way of working and a new kind of language
00:42:57,700 --> 00:43:03,100
of research where you're more interested in different people's viewpoints, different people's lived experiences.
00:43:03,100 --> 00:43:10,120
And it's not necessarily about the number of times somebody says something and trying to get out of that purely quantitative mindset.
00:43:10,120 --> 00:43:15,460
It's as well as about, you know, the different range of experiences people are having and whether that's something that is
00:43:15,460 --> 00:43:19,810
interesting and meaningful to your research and could be taken forward to explore more.
00:43:19,810 --> 00:43:25,540
Certainly. I was just going to say it's hard to get out of the quantitative mindset initially because, you know,
00:43:25,540 --> 00:43:31,540
when we were first approaching it, we were trying to define how many times or how many participants have said a certain thing.
00:43:31,540 --> 00:43:39,220
But then you've explained to us, you know, actually that's not very useful way of approaching things in qualitative research,
00:43:39,220 --> 00:43:44,950
because just because half of the people in this interview said this doesn't mean that half of the
00:43:44,950 --> 00:43:51,670
people in the general public would say this or we're not approaching generalisability in the same way.
00:43:51,670 --> 00:43:56,530
Yeah, exactly. And the other thing that's really tricky, because obviously, if you use and say an in-depth interview,
00:43:56,530 --> 00:44:02,950
it might be that because obviously with a certain of certainly structured interviews, you don't always follow exactly the same interview questions.
00:44:02,950 --> 00:44:09,760
So it might be that some people had the opportunity because they were asked or it just went down the avenue to talk about their views on something.
00:44:09,760 --> 00:44:14,500
So they expressed it, whereas the other people in the other half of interviews might have had the opportunity, say,
00:44:14,500 --> 00:44:17,950
rather than them not necessarily agreeing or bringing up as meaningful,
00:44:17,950 --> 00:44:21,850
it might not have just been part of the questions, whereas it was a questionnaire.
00:44:21,850 --> 00:44:25,780
Everybody's getting exactly the same things that you can kind of compare it.
00:44:25,780 --> 00:44:29,050
So I it's just getting used to that different way of thinking about things.
00:44:29,050 --> 00:44:36,250
But it is tricky because, you know, it can sometimes be interesting that every single person thinks something versus nobody.
00:44:36,250 --> 00:44:40,150
But, yeah, it's just getting that balance, isn't it, and thinking about it in a new way.
00:44:40,150 --> 00:44:41,950
Yeah, yeah, definitely.
00:44:41,950 --> 00:44:51,910
So if we were to think a little bit about our philosophical position before approaching a qualitative research or more specifically thematic analysis,
00:44:51,910 --> 00:44:56,440
do you think it's important to define this before starting with analysis?
00:44:56,440 --> 00:45:02,350
And what how would you define your philosophical position? That's really difficult question to ask.
00:45:02,350 --> 00:45:05,860
That's a very good yeah. So I think in terms of yeah, there's all these different words,
00:45:05,860 --> 00:45:11,560
people can get quite confused about the symbology and ontology and philosophy, philosophical positions.
00:45:11,560 --> 00:45:17,800
But I think a lot of it's about thinking about, OK, so what am I trying to find, am I like inductive?
00:45:17,800 --> 00:45:21,550
So am I really driven by my data and what people are saying?
00:45:21,550 --> 00:45:26,750
The participants are saying and I'm quite open or am I more deductive and more theory based?
00:45:26,750 --> 00:45:34,420
So, for example, if I was doing a search, this is a nice paper that looks at social identity approach to food banks and social psychology.
00:45:34,420 --> 00:45:42,490
And so that would be very much like a theoretical theoretical basis where you you're very much looking for social identity that would help explain it.
00:45:42,490 --> 00:45:49,660
So I think they're having this different theoretical position, whether you're very much data driven or theory driven,
00:45:49,660 --> 00:45:53,350
can influence as well the questions that you ask people in your interview.
00:45:53,350 --> 00:46:00,880
So in some cases, you know, defining that in advance can be important, but it kind of depends on the stage that you get the data,
00:46:00,880 --> 00:46:06,330
if you see what I mean, and other people, you know, use different kind of methods.
00:46:06,330 --> 00:46:12,640
So if you're using like this, we're talking about thematic analysis, for example, discourse analysis.
00:46:12,640 --> 00:46:16,480
If you're looking at the way things are constructed in language versus you've got
00:46:16,480 --> 00:46:20,980
like a more straightforward view of what the language is and what people say.
00:46:20,980 --> 00:46:28,240
And that's a more like essentialist position. I guess in the past that I've had more essentialist realist one and more inductive approach.
00:46:28,240 --> 00:46:31,660
So it's kind of you're just open to what the people are saying.
00:46:31,660 --> 00:46:37,520
And that's kind of a straightforward relationship between what they say and what you're writing.
00:46:37,520 --> 00:46:43,750
But, yeah, I think just being aware that it's more complex than the being one type of thematic analysis of them,
00:46:43,750 --> 00:46:50,140
all these different positions that people take that can lead to quite different analyses and quite different results,
00:46:50,140 --> 00:46:53,570
I think is is beneficial really when you're doing the work.
00:46:53,570 --> 00:47:01,600
So and we talk specifically about small q and big Q, which feeds into these kind of debates as well.
00:47:01,600 --> 00:47:05,800
So yeah, I was about to ask that. So yeah, that was something that we discussed.
00:47:05,800 --> 00:47:12,500
And some are reading this idea between the big Q qualitative research versus small qq ualitative research.
00:47:12,500 --> 00:47:16,540
So I wondered, yeah. If you can tell us a little bit more about that.
00:47:16,540 --> 00:47:24,280
So that I think was Killoran Fine. And that comes into the idea that you're doing like a project from a so if you're doing a big key,
00:47:24,280 --> 00:47:29,590
one is from like a qualitative background, a qualitative like philosophy.
00:47:29,590 --> 00:47:36,460
And your it's what broaden out talk about the organic reflexive one is like a big key one because you're just very
00:47:36,460 --> 00:47:42,190
open to all the participants are saying you don't think that you have to count the number of times things happen.
00:47:42,190 --> 00:47:51,370
It's very iterative. Your you know, you're recognising that the researcher as an analyst is very involved in interpreting the data,
00:47:51,370 --> 00:47:59,980
whereas like a small q one is much more in line with, like quantitative thinking, thinking that you'd have to maybe, you know,
00:47:59,980 --> 00:48:05,110
like a kind of more like a kind of qualitative content analysis where you were counting the number of times something
00:48:05,110 --> 00:48:11,440
happened that you had like an idea beforehand of what exactly you were going to count before you even saw the data.
00:48:11,440 --> 00:48:14,290
You'd know what you were going to count or not, and then you'd count that thing.
00:48:14,290 --> 00:48:21,130
And that would be a much more small, cute sample because you're not really doing the research from a very qualitative philosophy in the sense that,
00:48:21,130 --> 00:48:26,440
you know, it's not so much about the participants lived experiences or being open to interpreting the findings.
00:48:26,440 --> 00:48:28,180
It's much more like closed off,
00:48:28,180 --> 00:48:33,760
like a questionnaire would be something that is much it's like a much more quantitative way to do qualitative research.
00:48:33,760 --> 00:48:43,420
So that's kind of part of the divide, I think within and it's not necessarily bad to do small q that could be exactly what you need in a study,
00:48:43,420 --> 00:48:52,240
but it is recognising that it is a very different approach from having much more open questions in your interviews and be much more
00:48:52,240 --> 00:49:00,850
open to following kind of lines of enquiry from the participant versus is this much more kind of closed off way of of doing it?
00:49:00,850 --> 00:49:05,890
And I guess this kind of shows in terms of thematic analysis, different approach,
00:49:05,890 --> 00:49:12,190
a thematic analysis kind of set along different ends of this continuum from big Q to small q research, is that right?
00:49:12,190 --> 00:49:14,200
Yeah, yeah, that's right. That's what they talk about.
00:49:14,200 --> 00:49:22,820
Some of the papers, this kind of codebook one or the more kind of content analysis or their reflexive organic one, which is like the big Q So it does.
00:49:22,820 --> 00:49:29,710
And that kind of middle that big ish q in the middle where you are some maybe predefined ideas in mind,
00:49:29,710 --> 00:49:36,400
but also you're open to what the participants are saying as well, which is kind of where I think the keramine paper sits in the middle.
00:49:36,400 --> 00:49:45,580
Yeah, I guess. Before we wrap up, do you have any other final thoughts or tips that you'd have for me, such as approaching qualitative research?
00:49:45,580 --> 00:49:48,220
Yeah, I guess just to be open to qualitative research,
00:49:48,220 --> 00:49:52,880
if you haven't done it before as a it's just I think most people that even if they haven't done it before,
00:49:52,880 --> 00:49:58,150
they're going to say to do find it intrinsically really interesting finding out more about their experiences,
00:49:58,150 --> 00:50:02,680
because it you know, compared to the questionnaire studies where you just really can't get much information
00:50:02,680 --> 00:50:05,890
from people about how they finding out how they're thinking about things.
00:50:05,890 --> 00:50:11,110
It does provide this other perspective, which I think is really valuable in so many areas of research.
00:50:11,110 --> 00:50:18,430
Yeah, definitely. I agree. I mean, I found that there was such a it sounds like quite a bit like a cliche, but it's such a deep insight.
00:50:18,430 --> 00:50:23,950
You're getting into people's experiences. And it was really interesting and informative study.
00:50:23,950 --> 00:50:32,920
Yeah. Thank you so much. Thanks for your advice. And yeah, I was really helpful for me and I'm sure it'll be helpful for the as well.
00:50:32,920 --> 00:50:37,270
Thank you. And that's it for this episode.
00:50:37,270 --> 00:50:42,600
Don't forget to like rare and subscribe and join us next time when we'll be talking to somebody else
00:50:42,600 --> 00:51:06,930
About research and everything in between.